Q12

## Create survey object.
options(digits = 4)
options(survey.lonely.psu = "adjust")
des <- svydesign(ids = ~1, weights = ~weight, data = df[is.na(df$weight)==F, ])

Q12. Which of the following actions do you take to avoid getting sick?

# subset question data, rename columns, gather into single column
q12_df <- df %>%
  select(CaseID, PPGENDER, PPAGE, ppagecat, PPETHM, PPINCIMP, PPEDUC, PPEDUCAT,
         work, PPWORK, marital, PPMARIT, PPMSACAT, ppreg9, PPSTATEN, PPHOUSE, PPRENT, PPNET, Q12_1:Q12_15, weight) %>%
    rename("Q12_1_Avoid.touching.my.eyes" = Q12_1,
         "Q12_2_Avoid.touching.my.nose" = Q12_2,
         "Q12_3_Avoid.touching.my.mouth" =  Q12_3,
         "Q12_4_Wash.my.hands.with.soap.more.often"= Q12_4,
         "Q12_5_Use.hand.sanitizers" = Q12_5,
         "Q12_6_Clean.the.surfaces.in.my.home" =    Q12_6,
         "Q12_7_Clean.the.surfaces.at.work" = Q12_7,
         "Q12_8_Eat.nutritious.food" = Q12_8,
         "Q12_9_Get.adequate.rest" = Q12_9,
         "Q12_10_Get.recommended.vaccine" = Q12_10,
         "Q12_11_Take.preventive.medicine" = Q12_11,
         "Q12_12_Cover.my.nose.and.mouth.with.a.surgical.mask" = Q12_12,
         "Q12_13_Avoid.contact.with.people.who.are.sick" = Q12_13,
         "Q12_14_Avoid.crowded.places" = Q12_14,
         "Q12_15_Other" = Q12_15) %>%
  gather(Q12_q, Q12_r, Q12_1_Avoid.touching.my.eyes:Q12_15_Other, na.rm = T) %>%
  mutate(Q12_q = as.factor(Q12_q)) %>%
  mutate(Q12_r = factor(Q12_r, levels = c("Always", "Sometimes", "Never")))
# survey design
options(digits = 4)
options(survey.lonely.psu = "adjust")
des12 <- svydesign(ids = ~1, weights = ~weight, data = q12_df[is.na(q12_df$weight)==F, ])

rr p2 + geom_bar() + aes(Q12_q, fill = PPGENDER) + facet_wrap(~Q12_r)

rr p2 + geom_bar() + aes(PPGENDER, fill = PPGENDER) + facet_grid(Q12_q~Q12_r) + coord_flip() + ptext2

rr p2 + geom_bar() + aes(Q12_q, fill = ppagecat) + facet_wrap(~Q12_r)

rr p2 + geom_bar() + aes(ppagecat, fill = ppagecat) + facet_grid(Q12_q~Q12_r) + ptext2

rr p2 + geom_bar() + aes(Q12_q, fill = PPETHM) + facet_wrap(~Q12_r)

rr p2 + geom_bar() + aes(PPETHM, fill = PPETHM) + facet_grid(Q12_q~Q12_r) + ptext2

rr p2 + geom_bar() + aes(Q12_r, fill = Q12_r) + facet_grid(Q12_q~PPETHM) + ptext2

rr p2 + geom_bar() + aes(Q12_q, fill = PPINCIMP) + facet_wrap(~Q12_r)

rr p2 + geom_bar() + aes(PPINCIMP, fill = PPINCIMP) + facet_grid(Q12_q~Q12_r) + ptext2

Education, work, marital status

rr # update weighted data frame q12.2 <- data.frame(svytable(~Q12_q + Q12_r + PPEDUC + PPEDUCAT + work + PPWORK + marital + PPMARIT, des12, round = T)) # restate plots p3 <- ggplot(q12.2, aes(Q12_q, weight = Freq)) + ptext

rr p3 + geom_bar() + aes(Q12_q, fill = PPEDUCAT) + facet_wrap(~Q12_r)

rr p3 + geom_bar() + aes(PPEDUCAT, fill = PPEDUCAT) + facet_grid(Q12_q~Q12_r) + ptext2

rr p3 + geom_bar() + aes(Q12_r, fill = Q12_r) + facet_grid(Q12_q~PPEDUCAT) + ptext2

Metro status, region, state, house type, housing status, internet availability

rr # update weighted data frame q12.3 <- data.frame(svytable(~Q12_q + Q12_r + PPMSACAT + ppreg9 + PPSTATEN + PPHOUSE + PPRENT + PPNET, des12, round = T)) # restate plots p4 <- ggplot(q12.3, aes(Q12_q, weight = Freq)) + ptext